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@Arcadia-Science

Arcadia Science

Welcome to @Arcadia-Science!

At Arcadia, one of our central tenets is that our science should be maximally useful. Computational tasks are embedded in all aspects of our scientific inquiry, so we need our computing strategies to be maximally useful too. What does this mean? In addition to aligning with scientific priorities across Arcadia, we believe that useful computing is ✨ innovative, 👩‍💻usable, 🔁 reproducible.

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  1. metagenomics metagenomics Public

    A Nextflow workflow for QC, evaluation, and profiling of metagenomic samples using short- and long-read technologies

    Nextflow 37 3

  2. ProteinCartography ProteinCartography Public

    a pipeline to build similarity maps of protein space

    Jupyter Notebook 37 11

  3. readlif readlif Public

    Leica Image Format (LIF) file reader for Python

    Python 36 13

  4. seqqc seqqc Public

    A Nextflow pipeline to identify quality control issues with new sequencing data.

    Groovy 28

  5. sourmashconsumr sourmashconsumr Public

    Working with the outputs of sourmash in R

    Standard ML 27 3

  6. 2023-nr-clustering 2023-nr-clustering Public

    Clustering the NCBI nr database with mmseq2 (90% length, 90% identity). Inspired by the NCBI's experimental ClusteredNR database.

    Python 23 2

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